This project focuses on forecasting wind power generation using data analysis and machine learning techniques. The notebook explores various predictive models to estimate wind power output based on historical data, weather conditions, and other relevant parameters.
✅ Data preprocessing and cleaning
✅ Exploratory Data Analysis (EDA) 📊
✅ Feature selection and engineering 🎯
✅ Model training and evaluation 🤖
✅ Forecasting wind power generation 🔮
Ensure you have the following dependencies installed:
pip install numpy pandas matplotlib seaborn scikit-learn1️⃣ Load the dataset and preprocess it
2️⃣ Perform exploratory data analysis 📈
3️⃣ Train different machine learning models 🤖
4️⃣ Evaluate performance using relevant metrics 📊
5️⃣ Generate forecasts for wind power output ⚡
The notebook presents visualizations, insights, and model performance comparisons to determine the best forecasting approach.
🚀🔥 Arsh